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AssigneeMicrosoft Corporation
InventorsYong Rui, Yunqiang Chen
Estimating the term…
A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
A system for tracking objects in sequential image frames comprising:
A computer-implemented process for probabilistically tracking at least one object throughout a sequence of images, comprising using a computer to:
A computer-readable medium having computer executable instructions for using a multi-hypothesis tracking system for automatically tracking a human head through at least two sequential image frames, said computer executable instructions comprising:
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